Functions for computing subscores for a test using different methods in both classical test theory (CTT) and item response theory (IRT). This package enables three sets of subscoring methods within the framework of CTT and IRT: Wainer's augmentation method, Haberman's three subscoring methods, and Yen's objective performance index (OPI). The package also includes the function to compute Proportional Reduction of Mean Squared Errors (PRMSEs) in Haberman's methods which are used to examine whether test subscores are of added value.
|Author||Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina [aut]|
|Date of publication||2016-12-03 00:53:13|
|Maintainer||Shenghai Dai <firstname.lastname@example.org>|
|License||GPL (>= 2)|
CTTsub: This main function estimates true subscores using different...
data.prep: This function prepares data into a requried list format
scored.data: Sample scored data
subscore.s: Computing subscores using Haberman's method based on observed...
subscore.sx: Computing subscores using Haberman's method based on both...
subscore.Wainer: Estimating true subscores using Wainer's augmentation method
subscore.x: Computing subscores using Haberman's method based on observed...
test.data: A list of objects that include both test information and...
Yen.OPI: Estimating true subscores using Yen's OPI
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